| Mining Fuzzy Coherent Rules from Quantitative Transactions Without Minimum Support Threshold | |
|---|---|
| 學年 | 100 |
| 學期 | 2 |
| 發表日期 | 2012-06-10 |
| 作品名稱 | Mining Fuzzy Coherent Rules from Quantitative Transactions Without Minimum Support Threshold |
| 作品名稱（其他語言） | |
| 著者 | Chne, Chun-hao; Li, Ai-fang; Lee, Yeong-chyi; Hong, Tzung-pei |
| 作品所屬單位 | 淡江大學資訊工程學系 |
| 出版者 | IEEE |
| 會議名稱 | Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on |
| 會議地點 | Brisbane, Australia |
| 摘要 | Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from the give quantitative transactions. However, some comment problems of those approaches are that (1) a minimum support should be predefined, and it is hard to set the appropriate one, and (2) the derived rules usually expose common-sense knowledge which may not be interested in business point of view. In this paper, we thus proposed an algorithm for mining fuzzy coherent rules to overcome those problems with the properties of propositional logic. It first transforms quantitative transactions into fuzzy sets. Then, those generated fuzzy sets are collected to generate candidate fuzzy coherent rules. Finally, contingency tables are calculated and used for checking those candidate fuzzy coherent rules satisfy four criteria or not. Experiments on the foodmart dataset are also made to show the effectiveness of the proposed algorithm. |
| 關鍵字 | data mining; fuzzy association rules; fuzzy coherent rules; fuzzy set; membership function |
| 語言 | en |
| 收錄於 | EI |
| 會議性質 | 國際 |
| 校內研討會地點 | |
| 研討會時間 | 20120610~20120615 |
| 通訊作者 | Chen, Chun-hao |
| 國別 | AUS |
| 公開徵稿 | Y |
| 出版型式 | |
| 出處 | Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on, pp.1779-1783 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/78105 ) |
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